Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda
Aturinde, Augustus LU ; Rose, Nakasi ; Farnaghi, Mahdi LU ; Maiga, Gilbert ; Pilesjö, Petter LU and Mansourian, Ali LU
(2019)
In BMC Medical Informatics and Decision Making
19(1).
p.215-215
- Abstract
BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.
METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the... (More)
BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.
METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.
RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.
CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.
(Less)
- author
- Aturinde, Augustus
LU
; Rose, Nakasi
; Farnaghi, Mahdi
LU
; Maiga, Gilbert
; Pilesjö, Petter
LU
and Mansourian, Ali
LU
- organization
- publishing date
- 2019-11-08
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Spatially-enabled health registry, SDI, RESTful web services, Spatial epidemiology, Mobile GIS, Uganda
- in
- BMC Medical Informatics and Decision Making
- volume
- 19
- issue
- 1
- pages
- 215 - 215
- publisher
- BioMed Central (BMC)
- external identifiers
-
- scopus:85074720866
- pmid:31703685
- ISSN
- 1472-6947
- DOI
- 10.1186/s12911-019-0949-y
- language
- English
- LU publication?
- yes
- id
- 0a271250-d766-45c6-9bf6-1037bdf3ded5
- date added to LUP
- 2019-11-15 10:54:06
- date last changed
- 2025-04-04 15:15:57
@article{0a271250-d766-45c6-9bf6-1037bdf3ded5,
abstract = {{<p>BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.</p><p>METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.</p><p>RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.</p><p>CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.</p>}},
author = {{Aturinde, Augustus and Rose, Nakasi and Farnaghi, Mahdi and Maiga, Gilbert and Pilesjö, Petter and Mansourian, Ali}},
issn = {{1472-6947}},
keywords = {{Spatially-enabled health registry; SDI; RESTful web services; Spatial epidemiology; Mobile GIS; Uganda}},
language = {{eng}},
month = {{11}},
number = {{1}},
pages = {{215--215}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Medical Informatics and Decision Making}},
title = {{Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda}},
url = {{http://dx.doi.org/10.1186/s12911-019-0949-y}},
doi = {{10.1186/s12911-019-0949-y}},
volume = {{19}},
year = {{2019}},
}